A Graph Approach for Enhancing Process Models Matchmaking
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Date
2015-06-27
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Recent attempts have been done to measure similarity of process models based on graph matching. This problem is known to be difficult and its computational complexity is exponential. Thus, heuristics should be proposed to obtain approximations.
Spectral graph matching methods, in particular eigenvalue-based projections, are know to be fast but they lost some quality in the obtained matchmaking. In this paper, we propose a graph approach for the problem of inexact matching of process models. Our approach combines a spectral graph matching method and a string comparator based algorithm in order to improve the quality of process models matchmaking.
The proposed method performs the matchmaking at both structural and semantic levels. Experimentation is provided to show the performance of our method to rank a collection of process models according to a particular user query, compared
to previous work.
Description
Keywords
Process models matchmaking, Process models retrieval, Spectral graph, Structural and semantic matching
Citation
2015 IEEE International Conference on Services Computing (SCC)